Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Listen to classical music;Exercise;Go to museums and galleries;Attend football matches;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Character.AI 
LLM use cases: Writing (e.g., composing emails);Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Digital content creation (e.g., creation of social media content);Analyze data 
Contexts of LLM use: School/University;Work;Personal;Learning 
Prompt 1: How does gender inequality manifest in the workplace?
Prompt 2: What are some of the most common challenges faced by women in leadership roles?
Prompt 3: How do societal expectations of gender impact mental health?
Prompt 4: What are the key differences between gender identity and biological sex?
Prompt 5: How can we create a more inclusive environment for all genders?
Prompt 6: What are the main causes of climate change?
Prompt 7: How do climate change and gender inequality intersect in vulnerable communities?
Prompt 8: What are some effective ways to reduce our carbon footprint?
Prompt 9: How does climate change affect biodiversity?
Prompt 10: What role do governments and businesses play in addressing climate change?
Comments: Surveys like this provide valuable insights into key social issues, and AI chatbots can be powerful tools for facilitating thoughtful discussions and expanding understanding on complex topics.